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Published January 2020 | Submitted
Journal Article Open

Constraining the vertical distribution of coastal dust aerosol using OCO-2 O₂ A-band measurements

Abstract

Quantifying the vertical distribution of atmospheric aerosols is crucial for estimating their impact on the Earth's energy budget and climate, improving forecast of air pollution in cities, and reducing biases in the retrieval of greenhouse gases (GHGs) from space. However, to date, passive remote sensing measurements have provided limited information about aerosol extinction profiles. In this study, we propose the use of a spectral sorting approach to constrain the aerosol vertical structure using spectra of reflected sunlight absorption within the molecular oxygen (O₂) A-band collected by the Orbiting Carbon Observatory-2 (OCO-2). The effectiveness of the approach is evaluated using spectra acquired over the western Sahara coast by comparing the aerosol profile retrievals with lidar measurements from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Using a radiative transfer model to simulate OCO-2 measurements, we found that high-resolution O₂ A-band measurements have high sensitivity to aerosol optical depth (AOD) and aerosol layer height (ALH). Retrieved estimates of AOD and ALH based on a look up table technique show good agreement with CALIPSO measurements, with correlation coefficients of 0.65 and 0.53, respectively. The strength of the proposed spectral sorting technique lies in its ability to identify spectral channels with high sensitivity to AOD and ALH and extract the associated information from the observed radiance in a straightforward manner. The proposed approach has the potential to enable future passive remote sensing missions to map the aerosol vertical distribution on a global scale.

Additional Information

© 2019 Elsevier Inc. Received 12 August 2019, Revised 19 October 2019, Accepted 23 October 2019, Available online 5 November 2019. We thank Run-Lie Shia at Caltech, Suniti Sanghavi at JPL, and Chao Liu at NUIST for stimulating discussions. The OCO-2 Forward model is available at https://github.com/nasa/RtRetrievalFramework. The L1bSc OCO-2 radiances are available online from the NASA Goddard GES DISC at https://disc. gsfc.nasa.gov/datacollection/OCO2_ L1B_Science_7.html. MERRAero monthly 3-h averaged dust column density data can be downloaded from (https://portal.nccs.nasa.gov/cgi-lats4d/webform.cgi?&i=GEOS-5/MERRAero/monthly/tavg3hr_2d_aer_Nx). S. C. acknowledges support from the SURF program at the California Institute of Technology and from the National University of Singapore. V. N. acknowledges support from the NASA Earth Science US Participating Investigator program (solicitation NNH16ZDA001N-ESUSPI). F. X. acknowledges support from the NASA Remote Sensing Theory program under grant 14-RST14-0100. A. M. acknowledges support from NASA grant award 80NSSC18K0891 as part of the NASA Science Team for the OCO missions. Z. C. Zeng would like to dedicate this paper to his newborn daughter Judy Zeng. We thank the support from the Jet Propulsion Laboratory Research and Technology Development Program. We also thank the three reviewers for their constructive comments and suggestions. Declaration of competing interest: None.

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